MARKET STUDY All analysis covers resale homes only. New construction appears once, in its own section. Click any dot on the map for that sale.
Resale sales, 365 days
30
single-family resale homes
Median net sale price
$392,860
average $385,799
Median net price per SF
$142
average $151
Median days on market
46 days
average 63 days
1. SummaryResale homes · 30 sales · November 5, 2025 – November 4, 2026
This study looks at the 30 resale homes sold in La Conterra in the 365 days to November 4, 2026. A full year is used because only 16 resale homes sold in the last 180 days. New construction is left out and shown on its own in section 7. The homes are compared four ways: by price, by living area, by year built and with or without a view. The first three are split into four equal groups (quartiles), each named by its range.
Each comparison has its own section (3–6) with everything about it in one place: the key differences, a table of every measure at a glance, the charts and the numbers.
2. Where the resale homes sold30 resale homes · colored by price range
Each dot is one resale home, colored by its price range. Use the buttons to show one price range at a time. Click a dot for that sale: address, close date, original and last list price, net sale price, living area, net sale per SF and days on market. Scroll or pinch to zoom.
3. Quartiles by net sale priceResale homes · 30 sales · November 5, 2025 – November 4, 2026
Sales ranked by net sale price and cut into four equal groups. This is the usual way to read a market by price.
Bottom line
Homes over $428K are about 1,510 SF (79%) larger than homes under $347K.
3.1 Key differences
The top group against the bottom group. Only real differences are listed. Section 8 explains each measure.
Under $347K$347K–$391K$395K–$428KOver $428K
Higher-priced homes Over $428K
Are much larger.
Lower-priced homes Under $347K
Are much smaller.
3.2 At a glance
Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.
Under $347K
$347K–$391K
$395K–$428K
Over $428K
Real difference?
Net price per SF
$171 per SF
$151 per SF
$146 per SF
$135 per SF
unclear
Living area
1,909 SFSmallest
2,455 SF
2,809 SF
3,422 SFLargest
✓ large
Year built
2016
2014
2016
2017
unclear
Days on market
56 days
28 days
41 days
40 days
unclear
Discount from original list
6.5%
4.4%
5.8%
4.3%
unclear
Price cut before sale
62%
14%
71%
38%
unclear
Seller paid closing costs or repairs
88%
86%
71%
62%
unclear
Has a view
0%
43%
14%
38%
unclear
How to read this section. Each heading gives the finding. The gold box says whether the gap is real (✓, with its size) or could be chance (–). The section ends with its numbers; the tests are in section 8.3.
3.3 Net price per SF: no clear difference
The average is $135 per SF for homes over $428K and $171 per SF for homes under $347K. It falls step by step from the lowest range to the highest. Defined in 8.1.2.
– No clear difference · could be chance
3.4 Homes over $428K are about 1,510 SF (79%) larger than homes under $347K
The average is 3,422 SF for homes over $428K and 1,909 SF for homes under $347K. It rises step by step from the lowest range to the highest. Defined in 8.1.3.
✓ Real difference · large
3.5 Year built: no clear difference
The median is 2017 for homes over $428K and 2016 for homes under $347K. It does not move in a straight line; homes over $428K are highest. Defined in 8.1.4.
– No clear difference · could be chance
3.6 Days on market: no clear difference
The median is 40 days for homes over $428K and 56 days for homes under $347K. It does not move in a straight line; homes under $347K are highest. Defined in 8.1.5.
– No clear difference · could be chance
3.7 Discount from original list: no clear difference
The average is 4.3% for homes over $428K and 6.5% for homes under $347K. It does not move in a straight line; homes under $347K are highest. Defined in 8.1.6.
– No clear difference · could be chance
3.8 How often: price cut before sale, seller paid closing costs or repairs, has a view
Each bar is the share of homes in the group, in percent.
38% of homes over $428K had a price cut before sale, against 62% of homes under $347K. Defined in 8.1.7.
62% of homes over $428K had the seller pay closing costs or repairs, against 88% of homes under $347K. Defined in 8.1.8.
38% of homes over $428K have a view, against 0% of homes under $347K. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance
3.9 The numbers: price and size
Under $347K8 sales
$347K–$391K7 sales
$395K–$428K7 sales
Over $428K8 sales
All30 sales
Real difference?
Net sale price average
$315,969
$358,931
$409,071
$458,775
$385,799
by design
Net price per SF average
$171
$151
$146
$135
$151
unclear
Living area average
1,909
2,455
2,809
3,422
2,650
✓ large
Year built median
2016
2014
2016
2017
2016
unclear
3.10 The numbers: selling
Under $347K8 sales
$347K–$391K7 sales
$395K–$428K7 sales
Over $428K8 sales
All30 sales
Real difference?
Days on market median
56
28
41
40
46
unclear
Discount from original list average
6.5%
4.4%
5.8%
4.3%
5.2%
unclear
Price cut before sale
62%
14%
71%
38%
47%
unclear
Seller paid closing costs or repairs
88%
86%
71%
62%
77%
unclear
Has a view
0%
43%
14%
38%
23%
unclear
Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.1.
4. Quartiles by living areaResale homes · 30 sales · November 5, 2025 – November 4, 2026
Sales ranked by living area and cut into four equal groups, from the smallest homes to the largest.
Bottom line
Homes over 3,010 SF sell for about $138K (43%) more than homes under 2,262 SF.
Homes over 3,010 SF sell for about $51 per SF (28%) less than homes under 2,262 SF.
4.1 Key differences
The top group against the bottom group. Only real differences are listed. Section 8 explains each measure.
Under 2,262 SF2,262–2,770 SF2,797–3,010 SFOver 3,010 SF
Larger homes Over 3,010 SF
Sell for much more.
Sell for less per square foot.
Smaller homes Under 2,262 SF
Sell for much less.
Sell for more per square foot.
4.2 At a glance
Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.
Under 2,262 SF
2,262–2,770 SF
2,797–3,010 SF
Over 3,010 SF
Real difference?
Net sale price
$318KLowest
$381K
$388K
$456KHighest
✓ large
Net price per SF
$184 per SFHighest
$150 per SF
$133 per SF
$133 per SFLowest
✓ large
Year built
2016
2013
2016
2016
unclear
Days on market
44 days
77 days
44 days
65 days
unclear
Discount from original list
4.8%
5.4%
6.3%
4.7%
unclear
Price cut before sale
50%
43%
57%
38%
unclear
Seller paid closing costs or repairs
88%
86%
57%
75%
unclear
Has a view
12%
14%
29%
38%
unclear
4.3 Homes over 3,010 SF sell for about $138K (43%) more than homes under 2,262 SF
The average is $456K for homes over 3,010 SF and $318K for homes under 2,262 SF. It rises step by step from the lowest range to the highest. Defined in 8.1.1.
✓ Real difference · large
4.4 Homes over 3,010 SF sell for about $51 per SF (28%) less than homes under 2,262 SF
The average is $133 per SF for homes over 3,010 SF and $184 per SF for homes under 2,262 SF. It falls step by step from the lowest range to the highest. Defined in 8.1.2.
✓ Real difference · large
4.5 Year built: no clear difference
The median is 2016 for homes over 3,010 SF and 2016 for homes under 2,262 SF. It does not move in a straight line; homes under 2,262 SF are highest. Defined in 8.1.4.
– No clear difference · could be chance
4.6 Days on market: no clear difference
The median is 65 days for homes over 3,010 SF and 44 days for homes under 2,262 SF. It does not move in a straight line; homes 2,262–2,770 SF are highest. Defined in 8.1.5.
– No clear difference · could be chance
4.7 Discount from original list: no clear difference
The average is 4.7% for homes over 3,010 SF and 4.8% for homes under 2,262 SF. It does not move in a straight line; homes 2,797–3,010 SF are highest. Defined in 8.1.6.
– No clear difference · could be chance
4.8 How often: price cut before sale, seller paid closing costs or repairs, has a view
Each bar is the share of homes in the group, in percent.
38% of homes over 3,010 SF had a price cut before sale, against 50% of homes under 2,262 SF. Defined in 8.1.7.
75% of homes over 3,010 SF had the seller pay closing costs or repairs, against 88% of homes under 2,262 SF. Defined in 8.1.8.
38% of homes over 3,010 SF have a view, against 12% of homes under 2,262 SF. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance
4.9 The numbers: price and size
Under 2,262 SF8 sales
2,262–2,770 SF7 sales
2,797–3,010 SF7 sales
Over 3,010 SF8 sales
All30 sales
Real difference?
Net sale price average
$317,925
$381,410
$387,786
$455,775
$385,799
✓ large
Net price per SF average
$184
$150
$133
$133
$151
✓ large
Living area average
1,733
2,556
2,904
3,427
2,650
by design
Year built median
2016
2013
2016
2016
2016
unclear
4.10 The numbers: selling
Under 2,262 SF8 sales
2,262–2,770 SF7 sales
2,797–3,010 SF7 sales
Over 3,010 SF8 sales
All30 sales
Real difference?
Days on market median
44
77
44
65
46
unclear
Discount from original list average
4.8%
5.4%
6.3%
4.7%
5.2%
unclear
Price cut before sale
50%
43%
57%
38%
47%
unclear
Seller paid closing costs or repairs
88%
86%
57%
75%
77%
unclear
Has a view
12%
14%
29%
38%
23%
unclear
Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.2.
5. Quartiles by year builtResale homes · 30 sales · November 5, 2025 – November 4, 2026
Sales ranked by year built and cut into four groups, from the oldest to the newest. Homes built in the same year always stay in the same group, so group sizes can differ a little.
Bottom line: no measure differs enough between the groups to rule out chance.
5.1 Key differences
The top group against the bottom group: no measure differs enough to rule out chance.
5.2 At a glance
Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.
Before 2014
2014–2015
2016–2018
After 2018
Real difference?
Net sale price
$366K
$408K
$396K
$378K
unclear
Net price per SF
$137 per SF
$135 per SF
$159 per SF
$167 per SF
unclear
Living area
2,716 SF
3,030 SF
2,586 SF
2,394 SF
unclear
Days on market
76 days
81 days
38 days
44 days
unclear
Discount from original list
6.2%
3.3%
3.8%
7.6%
unclear
Price cut before sale
38%
20%
30%
100%
unclear
Seller paid closing costs or repairs
88%
80%
70%
71%
unclear
Has a view
12%
40%
30%
14%
unclear
5.3 Net sale price: no clear difference
The average is $378K for homes built after 2018 and $366K for homes built before 2014. It does not move in a straight line; homes built 2014–2015 are highest. Defined in 8.1.1.
– No clear difference · could be chance
5.4 Net price per SF: no clear difference
The average is $167 per SF for homes built after 2018 and $137 per SF for homes built before 2014. It does not move in a straight line; homes built after 2018 are highest. Defined in 8.1.2.
– No clear difference · could be chance
5.5 Living area: no clear difference
The average is 2,394 SF for homes built after 2018 and 2,716 SF for homes built before 2014. It does not move in a straight line; homes built 2014–2015 are highest. Defined in 8.1.3.
– No clear difference · could be chance
5.6 Days on market: no clear difference
The median is 44 days for homes built after 2018 and 76 days for homes built before 2014. It does not move in a straight line; homes built 2014–2015 are highest. Defined in 8.1.5.
– No clear difference · could be chance
5.7 Discount from original list: no clear difference
The average is 7.6% for homes built after 2018 and 6.2% for homes built before 2014. It does not move in a straight line; homes built after 2018 are highest. Defined in 8.1.6.
– No clear difference · could be chance
5.8 How often: price cut before sale, seller paid closing costs or repairs, has a view
Each bar is the share of homes in the group, in percent.
100% of homes built after 2018 had a price cut before sale, against 38% of homes built before 2014. Defined in 8.1.7.
71% of homes built after 2018 had the seller pay closing costs or repairs, against 88% of homes built before 2014. Defined in 8.1.8.
14% of homes built after 2018 have a view, against 12% of homes built before 2014. Defined in 8.1.9.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
Has a view: – No clear difference · could be chance
5.9 The numbers: price and size
Before 20148 sales
2014–20155 sales
2016–201810 sales
After 20187 sales
All30 sales
Real difference?
Net sale price average
$366,296
$407,680
$395,820
$378,143
$385,799
unclear
Net price per SF average
$137
$135
$159
$167
$151
unclear
Living area average
2,716
3,030
2,586
2,394
2,650
unclear
Year built median
2012
2015
2016
2019
2016
by design
5.10 The numbers: selling
Before 20148 sales
2014–20155 sales
2016–201810 sales
After 20187 sales
All30 sales
Real difference?
Days on market median
76
81
38
44
46
unclear
Discount from original list average
6.2%
3.3%
3.8%
7.6%
5.2%
unclear
Price cut before sale
38%
20%
30%
100%
47%
unclear
Seller paid closing costs or repairs
88%
80%
70%
71%
77%
unclear
Has a view
12%
40%
30%
14%
23%
unclear
Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.3.
6. View and no viewResale homes · 30 sales · November 5, 2025 – November 4, 2026
Sales where the MLS lists a view (greenbelt or park, trees, golf course, hill country, water and similar) against those listing none or only the neighborhood.
Bottom line: no measure differs enough between the groups to rule out chance.
6.1 Key differences
The top group against the bottom group: no measure differs enough to rule out chance.
6.2 At a glance
Shaded rows are real differences; the darkest cell is the highest. Gray rows show no clear difference. Prices are averages; days on market and year built are medians.
View
No view
Real difference?
Net sale price
$418K
$376K
unclear
Net price per SF
$152 per SF
$151 per SF
unclear
Living area
2,816 SF
2,599 SF
unclear
Year built
2016
2016
unclear
Days on market
25 days
51 days
unclear
Discount from original list
3.9%
5.6%
unclear
Price cut before sale
43%
48%
unclear
Seller paid closing costs or repairs
86%
74%
unclear
6.3 Net sale price: no clear difference
The average is $418K for homes with a view and $376K for homes without a view. Defined in 8.1.1.
– No clear difference · could be chance
6.4 Net price per SF: no clear difference
The average is $152 per SF for homes with a view and $151 per SF for homes without a view. Defined in 8.1.2.
– No clear difference · could be chance
6.5 Living area: no clear difference
The average is 2,816 SF for homes with a view and 2,599 SF for homes without a view. Defined in 8.1.3.
– No clear difference · could be chance
6.6 Year built: no clear difference
The median is 2016 for homes with a view and 2016 for homes without a view. Defined in 8.1.4.
– No clear difference · could be chance
6.7 Days on market: no clear difference
The median is 25 days for homes with a view and 51 days for homes without a view. Defined in 8.1.5.
– No clear difference · could be chance
6.8 Discount from original list: no clear difference
The average is 3.9% for homes with a view and 5.6% for homes without a view. Defined in 8.1.6.
– No clear difference · could be chance
6.9 How often: price cut before sale, seller paid closing costs or repairs
Each bar is the share of homes in the group, in percent.
43% of homes with a view had a price cut before sale, against 48% of homes without a view. Defined in 8.1.7.
86% of homes with a view had the seller pay closing costs or repairs, against 74% of homes without a view. Defined in 8.1.8.
Price cut before sale: – No clear difference · could be chance
Seller paid closing costs or repairs: – No clear difference · could be chance
6.10 The numbers: price and size
View7 sales
No view23 sales
All30 sales
Real difference?
Net sale price average
$418,131
$375,959
$385,799
unclear
Net price per SF average
$152
$151
$151
unclear
Living area average
2,816
2,599
2,650
unclear
Year built median
2016
2016
2016
unclear
6.11 The numbers: selling
View7 sales
No view23 sales
All30 sales
Real difference?
Days on market median
25
51
46
unclear
Discount from original list average
3.9%
5.6%
5.2%
unclear
Price cut before sale
43%
48%
47%
unclear
Seller paid closing costs or repairs
86%
74%
77%
unclear
Prices, price per SF, living area and discount are averages; days on market and year built are medians. The test behind each verdict is in 8.3.4.
7. New constructionBasic statistics · 0 sales · November 5, 2025 – November 4, 2026
Homes sold new by the builder in the same 365 days. They are left out of every other section and shown here as basic figures only: 0 sales, no groups, no tests.
Note: these are only the new-construction sales reported in ABOR MLS. Builders often sell homes without listing them in the MLS, so these figures do not necessarily represent all new-construction sales in La Conterra.
No new-construction sales were reported in ABOR MLS in this window.
Same definitions as the rest of the study (section 8). New construction = NewConstructionYN true, or PropertyCondition “New Construction” or “Under Construction”.
8. AppendixMeasures, methods and tests
Each measure and method three ways: in plain words, as statistics, and with the data from this study.
8.1 Measures
8.1.1 Net sale price
In simple terms
What the seller actually kept: the closing price, less money the seller gave back to the buyer for closing costs or repairs. It is the truest price for comparing homes.
Statistically
Net = ClosePrice − ACTRIS_BuyersClsgCostPdbySell − ACTRIS_RepairsAmount (a blank counts as $0). Summarized by the arithmetic mean in the slices.
The data
30 resale sales. Average $385,799; median $392,860; standard deviation $59,864; middle half (25th–75th percentile) $343,325–$431,125; lowest $253,000, highest $494,000. 23 sales had a seller payment; their median payment was $7,000.
8.1.2 Net price per SF
In simple terms
Net sale price divided by the heated and cooled square feet. It puts homes of different sizes on the same footing: did buyers pay more for each square foot, not just for more square feet?
Statistically
psf = Net ÷ LivingArea, per sale; summarized by the mean of the per-sale ratios.
The data
30 resale sales. Average $151; median $142; standard deviation $26; middle half (25th–75th percentile) $134–$173; lowest $118, highest $207.
8.1.3 Living area
In simple terms
The heated and cooled space, as listed in the MLS. Garages and porches are not counted.
Statistically
RESO LivingArea, in square feet. Sales under 400 SF are treated as entry errors and left out.
The data
30 resale sales. Average 2,650; median 2,784; standard deviation 666; middle half (25th–75th percentile) 1,996–3,040; lowest 1,381, highest 3,690.
8.1.4 Year built
In simple terms
The year the home was finished, as listed in the MLS. It shows whether a group leans to older or newer phases of the community.
Statistically
RESO YearBuilt; summarized by the median, with the 25th–75th percentile (middle half) on the charts.
The data
30 resale sales. Average 2016; median 2016; standard deviation 3; middle half (25th–75th percentile) 2013–2018; lowest 2008, highest 2021.
8.1.5 Days on market
In simple terms
How many days the home was on the market before the buyer's offer was accepted, counting any earlier listing periods (relists). This is the days on market agents and clients quote.
Statistically
CDOM = max(CumulativeDaysOnMarket, DaysOnMarket, PurchaseContractDate − ListingContractDate). The MLS counter can freeze at a price change, so the contract-date gap is a floor. Summarized by the median, because a few homes that sat for months pull an average up.
The data
30 resale sales. Average 63; median 46; standard deviation 59; middle half (25th–75th percentile) 24–80; lowest 4, highest 222. 0 sales went under contract on their listing date (0 days).
8.1.6 Discount from original list
In simple terms
How far below the first asking price the home sold, after seller payments. It measures how much negotiating room sellers gave up. A negative figure means the home sold above its first asking price.
Statistically
Discount % = (OriginalListPrice − Net) ÷ OriginalListPrice × 100, per sale; summarized by the mean.
The data
30 resale sales. Average 5.2%; median 3.8%; standard deviation 4.4%; middle half (25th–75th percentile) 2.0%–7.2%; lowest −0.7%, highest 18.4%. 1 sales closed above their first asking price.
8.1.7 Price cut before sale
In simple terms
The asking price was lowered at least once before the home went under contract.
Statistically
Indicator: ListPrice at close < OriginalListPrice. Reported as the share of sales (%).
The data
14 of 30 resale sales (46.7%).
8.1.8 Seller paid closing costs or repairs
In simple terms
The seller paid some of the buyer's closing costs or repairs.
Statistically
Indicator: ACTRIS_BuyersClsgCostPdbySell + ACTRIS_RepairsAmount > 0. Reported as the share of sales (%).
The data
23 of 30 resale sales (76.7%).
8.1.9 Has a view
In simple terms
The MLS says the home looks over something: a greenbelt or park, trees, golf course, hill country, water and similar.
Statistically
View = the View field holds any entry other than “None”, “Neighborhood” or “See Remarks”. No view = only “None” and/or “Neighborhood”. A record whose only entry is “See Remarks” cannot be classified and is left out of the view slice.
The data
7 sales with a view, 23 without, 0 unclassified. Most common View entries: None 14, Neighborhood 11, Trees/Woods 4, Park/Greenbelt 4, Garden 1.
8.2 Methods
8.2.1 Data source
In simple terms
Every figure comes from the Austin Board of REALTORS® MLS, read live by ALEX. No figure is estimated or typed in.
Statistically
ABOR MLS via secure APIs, read from ALEX's copy of the MLS (refreshed every 15 minutes; this pull as of 2026-11-05 22:15 UTC), every field. Filter: StandardStatus = Closed, PropertyType = Residential, City = Georgetown, SubdivisionName contains any of “la conterra”, “la conterra north” (case-insensitive). A record is kept when its subdivision name belongs to the La Conterra family, the same rule comparable sales use (it includes La Conterra North Ph 2, proven adjacent and priced alike).
The data
Pulled November 5, 2026: 30 closed La Conterra records over the prior year, in ZIP 78626. 14 subdivision spellings kept, the most common: La Conterra (7); La Conterra Sub Sec 7 (6); La Conterra Sec 01 (4); La Conterra Sec 2 (2); La Conterra North Ph 2 (2); La Conterra Sec 7 (1); La Conterra Sub Sec 5 (1); LA CONTERRA SUB SEC 2 (1); La Conterra Sub Sec 2 (1); LA CONTERRA NORTH (1); La Conterra North (1); La Conterra Sec 6 (1); and 2 more (2 records). No other names were found by the search.
8.2.2 Study window
In simple terms
The most recent 365 days of closed sales: recent enough to describe today's market, long enough to give each group plenty of sales. The usual window is 180 days; it holds only 16 resale sales here (under 80), so the full year is used.
Statistically
CloseDate from November 5, 2025 to November 4, 2026 inclusive.
The data
30 single-family sales in the window: 30 resale, 0 new construction.
8.2.3 Resale and new construction
In simple terms
A resale home was previously owned. New construction is sold by the builder and behaves differently, so it is kept out of every analysis and reported once on its own.
Statistically
New construction = NewConstructionYN true, or PropertyCondition contains “New Construction” or “Under Construction”. Everything else is resale.
The data
30 resale; 0 new construction.
8.2.4 Sales left out
In simple terms
A few records cannot be used as entered and are left out before any analysis.
Statistically
Excluded: PropertySubType other than Single Family Residence; no OriginalListPrice; LivingArea under 400 SF; seller payments above 10% of ClosePrice (treated as entry errors).
The data
None in this window.
8.2.5 Quartiles and groups
In simple terms
Sales lined up from lowest to highest and cut into four groups of about equal size. Each group is named by its range, for example “Under $347K”.
Statistically
Sort by the slicing variable; cut k sits at round(nk/4), k = 1…3. A cut that would split tied values moves to the nearer edge of the tie. A group under 3 sales merges into its smaller neighbor. Range names use the next group's lowest value (“Under”) and the previous group's highest value (“Over”/“After”).
The data
Quartiles by net sale price: Under $347K: $253,000–$342,000 (8 sales); $347K–$391K: $347,300–$390,720 (7 sales); $395K–$428K: $395,000–$428,500 (7 sales); Over $428K: $432,000–$494,000 (8 sales) Quartiles by living area: Under 2,262 SF: 1,381–1,908 SF (8 sales); 2,262–2,770 SF: 2,262–2,770 SF (7 sales); 2,797–3,010 SF: 2,797–3,010 SF (7 sales); Over 3,010 SF: 3,050–3,690 SF (8 sales) Quartiles by year built: Before 2014: 2008–2013 (8 sales); 2014–2015: 2014–2015 (5 sales); 2016–2018: 2016–2018 (10 sales); After 2018: 2019–2021 (7 sales) View and no view: View: MLS lists a view (7 sales); No view: None or Neighborhood (23 sales)
8.2.6 Average and median
In simple terms
The average adds the values and divides by how many; one very expensive home can pull it up. The median is the middle value, with half above and half below.
Statistically
Mean x̄ = (1/n) Σ xᵢ; median = 50th percentile. Price, price per SF, living area and discount use the mean; days on market and year built use the median (skewed or whole-year values).
The data
Net sale price: average $385,799, median $392,860. Days on market: average 63, median 46: the average is pulled up by a few long listings.
8.2.7 Kruskal–Wallis test
In simple terms
Checks whether a measure really differs across the four groups of a slice. It uses each sale's rank, not its value, so a few extreme sales cannot drive the answer.
Statistically
H = [12/(n(n+1))] Σ Rⱼ²/nⱼ − 3(n+1), compared with χ² on k − 1 degrees of freedom (Kruskal & Wallis, 1952). Effect size ε² = H/(n − 1): ≥ .01 small, ≥ .06 medium, ≥ .14 large (Tomczak & Tomczak, 2014). A slice is tested only when every group has at least 5 sales; smaller groups are described, not tested.
The data
Run on every measure in sections 3–5; each result is in 8.3.
8.2.8 Mann–Whitney U test
In simple terms
The same check when there are only two groups: view against no view.
Statistically
Two-sided U test (Mann & Whitney, 1947). Effect size = rank-biserial correlation |1 − 2U/(n₁n₂)|: ≥ .10 small, ≥ .30 medium, ≥ .50 large (Kerby, 2014; Cohen, 1988).
The data
Run on every measure in section 6; results in 8.3.
8.2.9 Chi-square test
In simple terms
Checks whether a yes/no share (price cut, seller payment, view) differs between groups more than chance would.
Statistically
Pearson χ² on the 2 × k table of counts, no continuity correction (Pearson, 1900). Effect size Cramér's V = √(χ²/n): ≥ .10 small, ≥ .30 medium, ≥ .50 large (Cramér, 1946).
The data
Run on the three shares in every slice; results in 8.3.
8.2.10 Real difference (significance)
In simple terms
“Real difference” means a gap this large would be very unlikely if the groups were really alike. Because many measures are checked in each slice, the bar is set higher than usual.
Statistically
Significant when p < 0.05 ÷ m, where m is the number of measures tested in that slice (Bonferroni; Dunn, 1961). The slicing variable itself differs by design and is not tested.
The data
Quartiles by net sale price: m = 8, threshold p < 0.0063; Quartiles by living area: m = 8, threshold p < 0.0063; Quartiles by year built: m = 8, threshold p < 0.0063; View and no view: m = 8, threshold p < 0.0063
8.2.11 Size of a difference
In simple terms
A difference can be real but small. The size word (small, medium, large) says how much the groups pull apart.
Statistically
ε² for Kruskal–Wallis, rank-biserial r for Mann–Whitney, Cramér's V for chi-square, with the thresholds above; below the small threshold the size is “negligible”.
The data
3 real differences across the four slices; sizes are listed in 8.3.
8.2.12 Rounding in the text
In simple terms
Headings and sentences round figures so they read easily; the tables at the end of each section give them in full.
Statistically
Prices in headings round to the nearest $1K; price per SF and days on market to the nearest whole number; living area to the nearest 10 SF; shares and percentage gaps to whole percents.
The data
Days on market is always shown in days.
8.3 Test results
Every test behind every gold box. Statistic, degrees of freedom (df), p-value, the threshold it must beat, and the size of the difference.
8.3.1 Quartiles by net sale price
Measure
Test
Statistic
df
p-value
Threshold
Real difference?
Effect size
Size
Net price per SF
Kruskal–Wallis
H = 6.12
3
0.1059
p < 0.0063
Unclear
ε² = 0.211
large
Living area
Kruskal–Wallis
H = 22.75
3
< 0.0001
p < 0.0063
Yes
ε² = 0.784
large
Year built
Kruskal–Wallis
H = 1.73
3
0.6313
p < 0.0063
Unclear
ε² = 0.059
small
Days on market
Kruskal–Wallis
H = 1.73
3
0.6308
p < 0.0063
Unclear
ε² = 0.060
small
Discount from original list
Kruskal–Wallis
H = 2.63
3
0.4527
p < 0.0063
Unclear
ε² = 0.091
medium
Price cut before sale
Chi-square
χ² = 5.75
3
0.1245
p < 0.0063
Unclear
Cramér’s V = 0.438
medium
Seller paid closing costs or repairs
Chi-square
χ² = 1.85
3
0.6041
p < 0.0063
Unclear
Cramér’s V = 0.248
small
Has a view
Chi-square
χ² = 5.14
3
0.1615
p < 0.0063
Unclear
Cramér’s V = 0.414
medium
8.3.2 Quartiles by living area
Measure
Test
Statistic
df
p-value
Threshold
Real difference?
Effect size
Size
Net sale price
Kruskal–Wallis
H = 22.56
3
< 0.0001
p < 0.0063
Yes
ε² = 0.778
large
Net price per SF
Kruskal–Wallis
H = 16.57
3
0.0009
p < 0.0063
Yes
ε² = 0.571
large
Year built
Kruskal–Wallis
H = 4.09
3
0.2519
p < 0.0063
Unclear
ε² = 0.141
large
Days on market
Kruskal–Wallis
H = 2.61
3
0.4554
p < 0.0063
Unclear
ε² = 0.090
medium
Discount from original list
Kruskal–Wallis
H = 2.69
3
0.4419
p < 0.0063
Unclear
ε² = 0.093
medium
Price cut before sale
Chi-square
χ² = 0.66
3
0.8837
p < 0.0063
Unclear
Cramér’s V = 0.148
small
Seller paid closing costs or repairs
Chi-square
χ² = 2.35
3
0.5032
p < 0.0063
Unclear
Cramér’s V = 0.280
small
Has a view
Chi-square
χ² = 1.85
3
0.6041
p < 0.0063
Unclear
Cramér’s V = 0.248
small
8.3.3 Quartiles by year built
Measure
Test
Statistic
df
p-value
Threshold
Real difference?
Effect size
Size
Net sale price
Kruskal–Wallis
H = 1.43
3
0.6983
p < 0.0063
Unclear
ε² = 0.049
small
Net price per SF
Kruskal–Wallis
H = 7.21
3
0.0656
p < 0.0063
Unclear
ε² = 0.248
large
Living area
Kruskal–Wallis
H = 3.03
3
0.3867
p < 0.0063
Unclear
ε² = 0.105
medium
Days on market
Kruskal–Wallis
H = 3.20
3
0.3623
p < 0.0063
Unclear
ε² = 0.110
medium
Discount from original list
Kruskal–Wallis
H = 4.49
3
0.2128
p < 0.0063
Unclear
ε² = 0.155
large
Price cut before sale
Chi-square
χ² = 10.81
3
0.0128
p < 0.0063
Unclear
Cramér’s V = 0.600
large
Seller paid closing costs or repairs
Chi-square
χ² = 0.91
3
0.8226
p < 0.0063
Unclear
Cramér’s V = 0.174
small
Has a view
Chi-square
χ² = 1.87
3
0.5998
p < 0.0063
Unclear
Cramér’s V = 0.250
small
8.3.4 View and no view
Measure
Test
Statistic
df
p-value
Threshold
Real difference?
Effect size
Size
Net sale price
Mann–Whitney U
U = 110.50
—
0.1480
p < 0.0063
Unclear
rank-biserial r = 0.373
medium
Net price per SF
Mann–Whitney U
U = 91.00
—
0.6314
p < 0.0063
Unclear
rank-biserial r = 0.130
small
Living area
Mann–Whitney U
U = 98.00
—
0.4131
p < 0.0063
Unclear
rank-biserial r = 0.217
small
Year built
Mann–Whitney U
U = 77.00
—
0.8824
p < 0.0063
Unclear
rank-biserial r = 0.043
negligible
Days on market
Mann–Whitney U
U = 53.00
—
0.1855
p < 0.0063
Unclear
rank-biserial r = 0.342
medium
Discount from original list
Mann–Whitney U
U = 64.00
—
0.4414
p < 0.0063
Unclear
rank-biserial r = 0.205
small
Price cut before sale
Chi-square
χ² = 0.05
1
0.8175
p < 0.0063
Unclear
Cramér’s V = 0.042
negligible
Seller paid closing costs or repairs
Chi-square
χ² = 0.42
1
0.5180
p < 0.0063
Unclear
Cramér’s V = 0.118
small
8.4 Data notes
Left out of the analysis: 0 new-construction sales (basic statistics only, section 7); nothing else. Statistics: Python, NumPy 2.5.3, SciPy 1.18.1.
8.5 References
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Erlbaum.
Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press.
Dunn, O. J. (1961). Multiple comparisons among means. JASA, 56(293), 52–64.
Kerby, D. S. (2014). The simple difference formula: an approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1.
Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. JASA, 47(260), 583–621.
Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60.
Pearson, K. (1900). On the criterion that a given system of deviations… Philosophical Magazine, 50(302), 157–175.
Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. Trends in Sport Sciences, 21(1), 19–25.